Data recovery services have become an important part of today's digital world. Many entities, especially those that create and store significant amounts of electronic data, rely on data recovery services to recover data from data backup storage media such as tapes, discs, disk drives, or other removable storage devices.
Recovering a large volume of electronic data typically involves processing many, in some cases, thousands of items of backup storage media. In practice, on the production floor, multiple large volumes of data recovery jobs may be processed coincidentally. Factors such as close temporal and spatial relationships among thousands of data media may cause incongruous, inconsistent, incorrect, or improper media items to be loaded into a job that they do not belong.
Currently, most data recovery services employ manual inspections to detect out of place media in a data recovery job. Human inspector(s) must manually check every physical media label and cross reference it against a master list for a particular data recovery job. This process is time-consuming, tedious, and potentially inaccurate. Moreover, even after manually checking every label, there is no guarantee that all data backup media loaded into a data recovery job are correct because a correct label could have been mistakenly applied on or otherwise attached to a wrong medium (e.g., a tape that is not a member of the backup job being recovered). In the event that a mistake (e.g., an incorrect medium) is found, it can cause an entire job to be re-executed, wasting time and money.
A need exists for a computer-implemented, automated data recovery system and method that can detect mistakes at various stages of a data recovery process, avoiding entirely or substantially reducing the probability of loading incongruous or incorrect media into a job that they do not belong. Embodiments of the present invention address this need and more.